Overview

Dataset statistics

Number of variables134
Number of observations4920
Missing cells4920
Missing cells (%)0.7%
Duplicate rows304
Duplicate rows (%)6.2%
Total size in memory5.0 MiB
Average record size in memory1.0 KiB

Variable types

Categorical133
Unsupported1

Alerts

fluid_overload has constant value "0" Constant
Dataset has 304 (6.2%) duplicate rowsDuplicates
nodal_skin_eruptions is highly correlated with dischromic _patchesHigh correlation
continuous_sneezing is highly correlated with shivering and 7 other fieldsHigh correlation
shivering is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
chills is highly correlated with high_fever and 2 other fieldsHigh correlation
stomach_pain is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
acidity is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
ulcers_on_tongue is highly correlated with stomach_pain and 1 other fieldsHigh correlation
muscle_wasting is highly correlated with patches_in_throat and 1 other fieldsHigh correlation
vomiting is highly correlated with nauseaHigh correlation
burning_micturition is highly correlated with spotting_ urination and 3 other fieldsHigh correlation
spotting_ urination is highly correlated with stomach_pain and 1 other fieldsHigh correlation
weight_gain is highly correlated with cold_hands_and_feets and 8 other fieldsHigh correlation
anxiety is highly correlated with blurred_and_distorted_vision and 3 other fieldsHigh correlation
cold_hands_and_feets is highly correlated with weight_gain and 8 other fieldsHigh correlation
mood_swings is highly correlated with weight_gain and 7 other fieldsHigh correlation
weight_loss is highly correlated with restlessnessHigh correlation
restlessness is highly correlated with weight_loss and 4 other fieldsHigh correlation
patches_in_throat is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
irregular_sugar_level is highly correlated with restlessness and 4 other fieldsHigh correlation
cough is highly correlated with breathlessness and 2 other fieldsHigh correlation
high_fever is highly correlated with chillsHigh correlation
sunken_eyes is highly correlated with dehydrationHigh correlation
breathlessness is highly correlated with cough and 3 other fieldsHigh correlation
sweating is highly correlated with breathlessness and 1 other fieldsHigh correlation
dehydration is highly correlated with sunken_eyesHigh correlation
indigestion is highly correlated with passage_of_gases and 2 other fieldsHigh correlation
yellowish_skin is highly correlated with dark_urine and 3 other fieldsHigh correlation
dark_urine is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
nausea is highly correlated with vomitingHigh correlation
loss_of_appetite is highly correlated with yellowish_skin and 1 other fieldsHigh correlation
pain_behind_the_eyes is highly correlated with back_pain and 1 other fieldsHigh correlation
back_pain is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
constipation is highly correlated with pain_during_bowel_movements and 5 other fieldsHigh correlation
abdominal_pain is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
mild_fever is highly correlated with swelled_lymph_nodes and 1 other fieldsHigh correlation
yellow_urine is highly correlated with receiving_blood_transfusion and 1 other fieldsHigh correlation
yellowing_of_eyes is highly correlated with yellowish_skin and 3 other fieldsHigh correlation
acute_liver_failure is highly correlated with coma and 1 other fieldsHigh correlation
swelling_of_stomach is highly correlated with distention_of_abdomen and 2 other fieldsHigh correlation
swelled_lymph_nodes is highly correlated with mild_fever and 9 other fieldsHigh correlation
malaise is highly correlated with chills and 3 other fieldsHigh correlation
blurred_and_distorted_vision is highly correlated with anxiety and 9 other fieldsHigh correlation
phlegm is highly correlated with chills and 13 other fieldsHigh correlation
throat_irritation is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
redness_of_eyes is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
sinus_pressure is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
runny_nose is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
congestion is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
chest_pain is highly correlated with cough and 2 other fieldsHigh correlation
weakness_in_limbs is highly correlated with back_pain and 3 other fieldsHigh correlation
fast_heart_rate is highly correlated with sweating and 1 other fieldsHigh correlation
pain_during_bowel_movements is highly correlated with constipation and 3 other fieldsHigh correlation
pain_in_anal_region is highly correlated with constipation and 3 other fieldsHigh correlation
bloody_stool is highly correlated with constipation and 3 other fieldsHigh correlation
irritation_in_anus is highly correlated with constipation and 3 other fieldsHigh correlation
neck_pain is highly correlated with weakness_in_limbs and 2 other fieldsHigh correlation
dizziness is highly correlated with weight_gain and 8 other fieldsHigh correlation
cramps is highly correlated with bruising and 4 other fieldsHigh correlation
bruising is highly correlated with cramps and 4 other fieldsHigh correlation
obesity is highly correlated with irregular_sugar_level and 7 other fieldsHigh correlation
swollen_legs is highly correlated with cramps and 4 other fieldsHigh correlation
swollen_blood_vessels is highly correlated with cramps and 4 other fieldsHigh correlation
puffy_face_and_eyes is highly correlated with weight_gain and 8 other fieldsHigh correlation
enlarged_thyroid is highly correlated with weight_gain and 8 other fieldsHigh correlation
brittle_nails is highly correlated with weight_gain and 8 other fieldsHigh correlation
swollen_extremeties is highly correlated with weight_gain and 8 other fieldsHigh correlation
excessive_hunger is highly correlated with restlessness and 2 other fieldsHigh correlation
extra_marital_contacts is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
drying_and_tingling_lips is highly correlated with anxiety and 3 other fieldsHigh correlation
slurred_speech is highly correlated with anxiety and 3 other fieldsHigh correlation
knee_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
hip_joint_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
muscle_weakness is highly correlated with movement_stiffnessHigh correlation
stiff_neck is highly correlated with movement_stiffness and 1 other fieldsHigh correlation
swelling_joints is highly correlated with knee_pain and 3 other fieldsHigh correlation
movement_stiffness is highly correlated with muscle_weakness and 3 other fieldsHigh correlation
spinning_movements is highly correlated with loss_of_balance and 1 other fieldsHigh correlation
loss_of_balance is highly correlated with weakness_in_limbs and 4 other fieldsHigh correlation
unsteadiness is highly correlated with spinning_movements and 1 other fieldsHigh correlation
weakness_of_one_body_side is highly correlated with altered_sensoriumHigh correlation
loss_of_smell is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
bladder_discomfort is highly correlated with burning_micturition and 2 other fieldsHigh correlation
foul_smell_of urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
continuous_feel_of_urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
passage_of_gases is highly correlated with indigestion and 1 other fieldsHigh correlation
internal_itching is highly correlated with indigestion and 1 other fieldsHigh correlation
toxic_look_(typhos) is highly correlated with constipation and 1 other fieldsHigh correlation
depression is highly correlated with weight_gain and 7 other fieldsHigh correlation
irritability is highly correlated with mood_swings and 4 other fieldsHigh correlation
altered_sensorium is highly correlated with weakness_of_one_body_sideHigh correlation
red_spots_over_body is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
belly_pain is highly correlated with constipation and 1 other fieldsHigh correlation
abnormal_menstruation is highly correlated with weight_gain and 7 other fieldsHigh correlation
dischromic _patches is highly correlated with nodal_skin_eruptionsHigh correlation
watering_from_eyes is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
increased_appetite is highly correlated with restlessness and 4 other fieldsHigh correlation
polyuria is highly correlated with restlessness and 4 other fieldsHigh correlation
family_history is highly correlated with mucoid_sputumHigh correlation
mucoid_sputum is highly correlated with family_historyHigh correlation
rusty_sputum is highly correlated with phlegm and 1 other fieldsHigh correlation
lack_of_concentration is highly correlated with dizziness and 1 other fieldsHigh correlation
visual_disturbances is highly correlated with acidity and 4 other fieldsHigh correlation
receiving_blood_transfusion is highly correlated with yellow_urine and 1 other fieldsHigh correlation
receiving_unsterile_injections is highly correlated with yellow_urine and 1 other fieldsHigh correlation
coma is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
stomach_bleeding is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
distention_of_abdomen is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
history_of_alcohol_consumption is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
fluid_overload.1 is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
blood_in_sputum is highly correlated with mild_fever and 2 other fieldsHigh correlation
prominent_veins_on_calf is highly correlated with cramps and 4 other fieldsHigh correlation
palpitations is highly correlated with anxiety and 3 other fieldsHigh correlation
painful_walking is highly correlated with knee_pain and 3 other fieldsHigh correlation
pus_filled_pimples is highly correlated with blackheads and 1 other fieldsHigh correlation
blackheads is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
scurring is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
skin_peeling is highly correlated with silver_like_dusting and 2 other fieldsHigh correlation
silver_like_dusting is highly correlated with skin_peeling and 2 other fieldsHigh correlation
small_dents_in_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
inflammatory_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
blister is highly correlated with red_sore_around_nose and 1 other fieldsHigh correlation
red_sore_around_nose is highly correlated with blister and 1 other fieldsHigh correlation
yellow_crust_ooze is highly correlated with blister and 1 other fieldsHigh correlation
nodal_skin_eruptions is highly correlated with dischromic _patchesHigh correlation
continuous_sneezing is highly correlated with shivering and 7 other fieldsHigh correlation
shivering is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
chills is highly correlated with high_fever and 2 other fieldsHigh correlation
stomach_pain is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
acidity is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
ulcers_on_tongue is highly correlated with stomach_pain and 1 other fieldsHigh correlation
muscle_wasting is highly correlated with patches_in_throat and 1 other fieldsHigh correlation
vomiting is highly correlated with nauseaHigh correlation
burning_micturition is highly correlated with spotting_ urination and 3 other fieldsHigh correlation
spotting_ urination is highly correlated with stomach_pain and 1 other fieldsHigh correlation
weight_gain is highly correlated with cold_hands_and_feets and 8 other fieldsHigh correlation
anxiety is highly correlated with blurred_and_distorted_vision and 3 other fieldsHigh correlation
cold_hands_and_feets is highly correlated with weight_gain and 8 other fieldsHigh correlation
mood_swings is highly correlated with weight_gain and 7 other fieldsHigh correlation
weight_loss is highly correlated with restlessnessHigh correlation
restlessness is highly correlated with weight_loss and 4 other fieldsHigh correlation
patches_in_throat is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
irregular_sugar_level is highly correlated with restlessness and 4 other fieldsHigh correlation
cough is highly correlated with breathlessness and 2 other fieldsHigh correlation
high_fever is highly correlated with chillsHigh correlation
sunken_eyes is highly correlated with dehydrationHigh correlation
breathlessness is highly correlated with cough and 3 other fieldsHigh correlation
sweating is highly correlated with breathlessness and 1 other fieldsHigh correlation
dehydration is highly correlated with sunken_eyesHigh correlation
indigestion is highly correlated with passage_of_gases and 2 other fieldsHigh correlation
yellowish_skin is highly correlated with dark_urine and 3 other fieldsHigh correlation
dark_urine is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
nausea is highly correlated with vomitingHigh correlation
loss_of_appetite is highly correlated with yellowish_skin and 1 other fieldsHigh correlation
pain_behind_the_eyes is highly correlated with back_pain and 1 other fieldsHigh correlation
back_pain is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
constipation is highly correlated with pain_during_bowel_movements and 5 other fieldsHigh correlation
abdominal_pain is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
mild_fever is highly correlated with swelled_lymph_nodes and 1 other fieldsHigh correlation
yellow_urine is highly correlated with receiving_blood_transfusion and 1 other fieldsHigh correlation
yellowing_of_eyes is highly correlated with yellowish_skin and 3 other fieldsHigh correlation
acute_liver_failure is highly correlated with coma and 1 other fieldsHigh correlation
swelling_of_stomach is highly correlated with distention_of_abdomen and 2 other fieldsHigh correlation
swelled_lymph_nodes is highly correlated with mild_fever and 9 other fieldsHigh correlation
malaise is highly correlated with chills and 3 other fieldsHigh correlation
blurred_and_distorted_vision is highly correlated with anxiety and 9 other fieldsHigh correlation
phlegm is highly correlated with chills and 13 other fieldsHigh correlation
throat_irritation is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
redness_of_eyes is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
sinus_pressure is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
runny_nose is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
congestion is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
chest_pain is highly correlated with cough and 2 other fieldsHigh correlation
weakness_in_limbs is highly correlated with back_pain and 3 other fieldsHigh correlation
fast_heart_rate is highly correlated with sweating and 1 other fieldsHigh correlation
pain_during_bowel_movements is highly correlated with constipation and 3 other fieldsHigh correlation
pain_in_anal_region is highly correlated with constipation and 3 other fieldsHigh correlation
bloody_stool is highly correlated with constipation and 3 other fieldsHigh correlation
irritation_in_anus is highly correlated with constipation and 3 other fieldsHigh correlation
neck_pain is highly correlated with weakness_in_limbs and 2 other fieldsHigh correlation
dizziness is highly correlated with weight_gain and 8 other fieldsHigh correlation
cramps is highly correlated with bruising and 4 other fieldsHigh correlation
bruising is highly correlated with cramps and 4 other fieldsHigh correlation
obesity is highly correlated with irregular_sugar_level and 7 other fieldsHigh correlation
swollen_legs is highly correlated with cramps and 4 other fieldsHigh correlation
swollen_blood_vessels is highly correlated with cramps and 4 other fieldsHigh correlation
puffy_face_and_eyes is highly correlated with weight_gain and 8 other fieldsHigh correlation
enlarged_thyroid is highly correlated with weight_gain and 8 other fieldsHigh correlation
brittle_nails is highly correlated with weight_gain and 8 other fieldsHigh correlation
swollen_extremeties is highly correlated with weight_gain and 8 other fieldsHigh correlation
excessive_hunger is highly correlated with restlessness and 2 other fieldsHigh correlation
extra_marital_contacts is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
drying_and_tingling_lips is highly correlated with anxiety and 3 other fieldsHigh correlation
slurred_speech is highly correlated with anxiety and 3 other fieldsHigh correlation
knee_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
hip_joint_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
muscle_weakness is highly correlated with movement_stiffnessHigh correlation
stiff_neck is highly correlated with movement_stiffness and 1 other fieldsHigh correlation
swelling_joints is highly correlated with knee_pain and 3 other fieldsHigh correlation
movement_stiffness is highly correlated with muscle_weakness and 3 other fieldsHigh correlation
spinning_movements is highly correlated with loss_of_balance and 1 other fieldsHigh correlation
loss_of_balance is highly correlated with weakness_in_limbs and 4 other fieldsHigh correlation
unsteadiness is highly correlated with spinning_movements and 1 other fieldsHigh correlation
weakness_of_one_body_side is highly correlated with altered_sensoriumHigh correlation
loss_of_smell is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
bladder_discomfort is highly correlated with burning_micturition and 2 other fieldsHigh correlation
foul_smell_of urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
continuous_feel_of_urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
passage_of_gases is highly correlated with indigestion and 1 other fieldsHigh correlation
internal_itching is highly correlated with indigestion and 1 other fieldsHigh correlation
toxic_look_(typhos) is highly correlated with constipation and 1 other fieldsHigh correlation
depression is highly correlated with weight_gain and 7 other fieldsHigh correlation
irritability is highly correlated with mood_swings and 4 other fieldsHigh correlation
altered_sensorium is highly correlated with weakness_of_one_body_sideHigh correlation
red_spots_over_body is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
belly_pain is highly correlated with constipation and 1 other fieldsHigh correlation
abnormal_menstruation is highly correlated with weight_gain and 7 other fieldsHigh correlation
dischromic _patches is highly correlated with nodal_skin_eruptionsHigh correlation
watering_from_eyes is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
increased_appetite is highly correlated with restlessness and 4 other fieldsHigh correlation
polyuria is highly correlated with restlessness and 4 other fieldsHigh correlation
family_history is highly correlated with mucoid_sputumHigh correlation
mucoid_sputum is highly correlated with family_historyHigh correlation
rusty_sputum is highly correlated with phlegm and 1 other fieldsHigh correlation
lack_of_concentration is highly correlated with dizziness and 1 other fieldsHigh correlation
visual_disturbances is highly correlated with acidity and 4 other fieldsHigh correlation
receiving_blood_transfusion is highly correlated with yellow_urine and 1 other fieldsHigh correlation
receiving_unsterile_injections is highly correlated with yellow_urine and 1 other fieldsHigh correlation
coma is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
stomach_bleeding is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
distention_of_abdomen is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
history_of_alcohol_consumption is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
fluid_overload.1 is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
blood_in_sputum is highly correlated with mild_fever and 2 other fieldsHigh correlation
prominent_veins_on_calf is highly correlated with cramps and 4 other fieldsHigh correlation
palpitations is highly correlated with anxiety and 3 other fieldsHigh correlation
painful_walking is highly correlated with knee_pain and 3 other fieldsHigh correlation
pus_filled_pimples is highly correlated with blackheads and 1 other fieldsHigh correlation
blackheads is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
scurring is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
skin_peeling is highly correlated with silver_like_dusting and 2 other fieldsHigh correlation
silver_like_dusting is highly correlated with skin_peeling and 2 other fieldsHigh correlation
small_dents_in_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
inflammatory_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
blister is highly correlated with red_sore_around_nose and 1 other fieldsHigh correlation
red_sore_around_nose is highly correlated with blister and 1 other fieldsHigh correlation
yellow_crust_ooze is highly correlated with blister and 1 other fieldsHigh correlation
nodal_skin_eruptions is highly correlated with dischromic _patchesHigh correlation
continuous_sneezing is highly correlated with shivering and 7 other fieldsHigh correlation
shivering is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
chills is highly correlated with high_fever and 2 other fieldsHigh correlation
stomach_pain is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
acidity is highly correlated with ulcers_on_tongue and 1 other fieldsHigh correlation
ulcers_on_tongue is highly correlated with stomach_pain and 1 other fieldsHigh correlation
muscle_wasting is highly correlated with patches_in_throat and 1 other fieldsHigh correlation
vomiting is highly correlated with nauseaHigh correlation
burning_micturition is highly correlated with spotting_ urination and 3 other fieldsHigh correlation
spotting_ urination is highly correlated with stomach_pain and 1 other fieldsHigh correlation
weight_gain is highly correlated with cold_hands_and_feets and 8 other fieldsHigh correlation
anxiety is highly correlated with blurred_and_distorted_vision and 3 other fieldsHigh correlation
cold_hands_and_feets is highly correlated with weight_gain and 8 other fieldsHigh correlation
mood_swings is highly correlated with weight_gain and 7 other fieldsHigh correlation
weight_loss is highly correlated with restlessnessHigh correlation
restlessness is highly correlated with weight_loss and 4 other fieldsHigh correlation
patches_in_throat is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
irregular_sugar_level is highly correlated with restlessness and 4 other fieldsHigh correlation
cough is highly correlated with breathlessness and 2 other fieldsHigh correlation
high_fever is highly correlated with chillsHigh correlation
sunken_eyes is highly correlated with dehydrationHigh correlation
breathlessness is highly correlated with cough and 3 other fieldsHigh correlation
sweating is highly correlated with breathlessness and 1 other fieldsHigh correlation
dehydration is highly correlated with sunken_eyesHigh correlation
indigestion is highly correlated with passage_of_gases and 2 other fieldsHigh correlation
yellowish_skin is highly correlated with dark_urine and 3 other fieldsHigh correlation
dark_urine is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
nausea is highly correlated with vomitingHigh correlation
loss_of_appetite is highly correlated with yellowish_skin and 1 other fieldsHigh correlation
pain_behind_the_eyes is highly correlated with back_pain and 1 other fieldsHigh correlation
back_pain is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
constipation is highly correlated with pain_during_bowel_movements and 5 other fieldsHigh correlation
abdominal_pain is highly correlated with yellowish_skin and 2 other fieldsHigh correlation
mild_fever is highly correlated with swelled_lymph_nodes and 1 other fieldsHigh correlation
yellow_urine is highly correlated with receiving_blood_transfusion and 1 other fieldsHigh correlation
yellowing_of_eyes is highly correlated with yellowish_skin and 3 other fieldsHigh correlation
acute_liver_failure is highly correlated with coma and 1 other fieldsHigh correlation
swelling_of_stomach is highly correlated with distention_of_abdomen and 2 other fieldsHigh correlation
swelled_lymph_nodes is highly correlated with mild_fever and 9 other fieldsHigh correlation
malaise is highly correlated with chills and 3 other fieldsHigh correlation
blurred_and_distorted_vision is highly correlated with anxiety and 9 other fieldsHigh correlation
phlegm is highly correlated with chills and 13 other fieldsHigh correlation
throat_irritation is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
redness_of_eyes is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
sinus_pressure is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
runny_nose is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
congestion is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
chest_pain is highly correlated with cough and 2 other fieldsHigh correlation
weakness_in_limbs is highly correlated with back_pain and 3 other fieldsHigh correlation
fast_heart_rate is highly correlated with sweating and 1 other fieldsHigh correlation
pain_during_bowel_movements is highly correlated with constipation and 3 other fieldsHigh correlation
pain_in_anal_region is highly correlated with constipation and 3 other fieldsHigh correlation
bloody_stool is highly correlated with constipation and 3 other fieldsHigh correlation
irritation_in_anus is highly correlated with constipation and 3 other fieldsHigh correlation
neck_pain is highly correlated with weakness_in_limbs and 2 other fieldsHigh correlation
dizziness is highly correlated with weight_gain and 8 other fieldsHigh correlation
cramps is highly correlated with bruising and 4 other fieldsHigh correlation
bruising is highly correlated with cramps and 4 other fieldsHigh correlation
obesity is highly correlated with irregular_sugar_level and 7 other fieldsHigh correlation
swollen_legs is highly correlated with cramps and 4 other fieldsHigh correlation
swollen_blood_vessels is highly correlated with cramps and 4 other fieldsHigh correlation
puffy_face_and_eyes is highly correlated with weight_gain and 8 other fieldsHigh correlation
enlarged_thyroid is highly correlated with weight_gain and 8 other fieldsHigh correlation
brittle_nails is highly correlated with weight_gain and 8 other fieldsHigh correlation
swollen_extremeties is highly correlated with weight_gain and 8 other fieldsHigh correlation
excessive_hunger is highly correlated with restlessness and 2 other fieldsHigh correlation
extra_marital_contacts is highly correlated with muscle_wasting and 1 other fieldsHigh correlation
drying_and_tingling_lips is highly correlated with anxiety and 3 other fieldsHigh correlation
slurred_speech is highly correlated with anxiety and 3 other fieldsHigh correlation
knee_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
hip_joint_pain is highly correlated with neck_pain and 3 other fieldsHigh correlation
muscle_weakness is highly correlated with movement_stiffnessHigh correlation
stiff_neck is highly correlated with movement_stiffness and 1 other fieldsHigh correlation
swelling_joints is highly correlated with knee_pain and 3 other fieldsHigh correlation
movement_stiffness is highly correlated with muscle_weakness and 3 other fieldsHigh correlation
spinning_movements is highly correlated with loss_of_balance and 1 other fieldsHigh correlation
loss_of_balance is highly correlated with weakness_in_limbs and 4 other fieldsHigh correlation
unsteadiness is highly correlated with spinning_movements and 1 other fieldsHigh correlation
weakness_of_one_body_side is highly correlated with altered_sensoriumHigh correlation
loss_of_smell is highly correlated with continuous_sneezing and 7 other fieldsHigh correlation
bladder_discomfort is highly correlated with burning_micturition and 2 other fieldsHigh correlation
foul_smell_of urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
continuous_feel_of_urine is highly correlated with burning_micturition and 2 other fieldsHigh correlation
passage_of_gases is highly correlated with indigestion and 1 other fieldsHigh correlation
internal_itching is highly correlated with indigestion and 1 other fieldsHigh correlation
toxic_look_(typhos) is highly correlated with constipation and 1 other fieldsHigh correlation
depression is highly correlated with weight_gain and 7 other fieldsHigh correlation
irritability is highly correlated with mood_swings and 4 other fieldsHigh correlation
altered_sensorium is highly correlated with weakness_of_one_body_sideHigh correlation
red_spots_over_body is highly correlated with pain_behind_the_eyes and 1 other fieldsHigh correlation
belly_pain is highly correlated with constipation and 1 other fieldsHigh correlation
abnormal_menstruation is highly correlated with weight_gain and 7 other fieldsHigh correlation
dischromic _patches is highly correlated with nodal_skin_eruptionsHigh correlation
watering_from_eyes is highly correlated with continuous_sneezing and 1 other fieldsHigh correlation
increased_appetite is highly correlated with restlessness and 4 other fieldsHigh correlation
polyuria is highly correlated with restlessness and 4 other fieldsHigh correlation
family_history is highly correlated with mucoid_sputumHigh correlation
mucoid_sputum is highly correlated with family_historyHigh correlation
rusty_sputum is highly correlated with phlegm and 1 other fieldsHigh correlation
lack_of_concentration is highly correlated with dizziness and 1 other fieldsHigh correlation
visual_disturbances is highly correlated with acidity and 4 other fieldsHigh correlation
receiving_blood_transfusion is highly correlated with yellow_urine and 1 other fieldsHigh correlation
receiving_unsterile_injections is highly correlated with yellow_urine and 1 other fieldsHigh correlation
coma is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
stomach_bleeding is highly correlated with acute_liver_failure and 1 other fieldsHigh correlation
distention_of_abdomen is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
history_of_alcohol_consumption is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
fluid_overload.1 is highly correlated with swelling_of_stomach and 2 other fieldsHigh correlation
blood_in_sputum is highly correlated with mild_fever and 2 other fieldsHigh correlation
prominent_veins_on_calf is highly correlated with cramps and 4 other fieldsHigh correlation
palpitations is highly correlated with anxiety and 3 other fieldsHigh correlation
painful_walking is highly correlated with knee_pain and 3 other fieldsHigh correlation
pus_filled_pimples is highly correlated with blackheads and 1 other fieldsHigh correlation
blackheads is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
scurring is highly correlated with pus_filled_pimples and 1 other fieldsHigh correlation
skin_peeling is highly correlated with silver_like_dusting and 2 other fieldsHigh correlation
silver_like_dusting is highly correlated with skin_peeling and 2 other fieldsHigh correlation
small_dents_in_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
inflammatory_nails is highly correlated with skin_peeling and 2 other fieldsHigh correlation
blister is highly correlated with red_sore_around_nose and 1 other fieldsHigh correlation
red_sore_around_nose is highly correlated with blister and 1 other fieldsHigh correlation
yellow_crust_ooze is highly correlated with blister and 1 other fieldsHigh correlation
constipation is highly correlated with belly_pain and 7 other fieldsHigh correlation
family_history is highly correlated with fluid_overload and 2 other fieldsHigh correlation
pus_filled_pimples is highly correlated with blackheads and 3 other fieldsHigh correlation
chills is highly correlated with high_fever and 4 other fieldsHigh correlation
yellow_urine is highly correlated with receiving_blood_transfusion and 3 other fieldsHigh correlation
bruising is highly correlated with fluid_overload and 6 other fieldsHigh correlation
abnormal_menstruation is highly correlated with brittle_nails and 9 other fieldsHigh correlation
continuous_feel_of_urine is highly correlated with foul_smell_of urine and 4 other fieldsHigh correlation
back_pain is highly correlated with weakness_in_limbs and 3 other fieldsHigh correlation
sweating is highly correlated with fast_heart_rate and 3 other fieldsHigh correlation
fast_heart_rate is highly correlated with sweating and 3 other fieldsHigh correlation
abdominal_pain is highly correlated with dark_urine and 4 other fieldsHigh correlation
redness_of_eyes is highly correlated with throat_irritation and 9 other fieldsHigh correlation
blackheads is highly correlated with pus_filled_pimples and 3 other fieldsHigh correlation
spinning_movements is highly correlated with loss_of_balance and 3 other fieldsHigh correlation
indigestion is highly correlated with passage_of_gases and 4 other fieldsHigh correlation
spotting_ urination is highly correlated with fluid_overload and 3 other fieldsHigh correlation
yellow_crust_ooze is highly correlated with fluid_overload and 3 other fieldsHigh correlation
weakness_in_limbs is highly correlated with back_pain and 5 other fieldsHigh correlation
increased_appetite is highly correlated with irregular_sugar_level and 6 other fieldsHigh correlation
itching is highly correlated with fluid_overload and 1 other fieldsHigh correlation
nausea is highly correlated with vomiting and 2 other fieldsHigh correlation
belly_pain is highly correlated with constipation and 3 other fieldsHigh correlation
muscle_weakness is highly correlated with fluid_overload and 2 other fieldsHigh correlation
dizziness is highly correlated with weakness_in_limbs and 10 other fieldsHigh correlation
skin_peeling is highly correlated with silver_like_dusting and 4 other fieldsHigh correlation
acute_liver_failure is highly correlated with fluid_overload and 3 other fieldsHigh correlation
throat_irritation is highly correlated with redness_of_eyes and 9 other fieldsHigh correlation
sunken_eyes is highly correlated with fluid_overload and 2 other fieldsHigh correlation
diarrhoea is highly correlated with fluid_overload and 1 other fieldsHigh correlation
high_fever is highly correlated with chills and 2 other fieldsHigh correlation
irregular_sugar_level is highly correlated with increased_appetite and 6 other fieldsHigh correlation
red_spots_over_body is highly correlated with fluid_overload and 3 other fieldsHigh correlation
loss_of_appetite is highly correlated with yellowing_of_eyes and 3 other fieldsHigh correlation
swelling_joints is highly correlated with painful_walking and 5 other fieldsHigh correlation
dark_urine is highly correlated with abdominal_pain and 4 other fieldsHigh correlation
dischromic _patches is highly correlated with fluid_overload and 2 other fieldsHigh correlation
passage_of_gases is highly correlated with indigestion and 3 other fieldsHigh correlation
painful_walking is highly correlated with swelling_joints and 5 other fieldsHigh correlation
watering_from_eyes is highly correlated with continuous_sneezing and 3 other fieldsHigh correlation
muscle_pain is highly correlated with fluid_overload and 1 other fieldsHigh correlation
vomiting is highly correlated with nausea and 2 other fieldsHigh correlation
depression is highly correlated with brittle_nails and 9 other fieldsHigh correlation
polyuria is highly correlated with increased_appetite and 6 other fieldsHigh correlation
phlegm is highly correlated with chills and 15 other fieldsHigh correlation
joint_pain is highly correlated with fluid_overload and 1 other fieldsHigh correlation
foul_smell_of urine is highly correlated with continuous_feel_of_urine and 4 other fieldsHigh correlation
drying_and_tingling_lips is highly correlated with slurred_speech and 5 other fieldsHigh correlation
slurred_speech is highly correlated with drying_and_tingling_lips and 5 other fieldsHigh correlation
continuous_sneezing is highly correlated with redness_of_eyes and 9 other fieldsHigh correlation
silver_like_dusting is highly correlated with skin_peeling and 4 other fieldsHigh correlation
blood_in_sputum is highly correlated with phlegm and 4 other fieldsHigh correlation
loss_of_balance is highly correlated with spinning_movements and 6 other fieldsHigh correlation
weight_loss is highly correlated with fluid_overload and 2 other fieldsHigh correlation
receiving_blood_transfusion is highly correlated with yellow_urine and 3 other fieldsHigh correlation
receiving_unsterile_injections is highly correlated with yellow_urine and 3 other fieldsHigh correlation
palpitations is highly correlated with drying_and_tingling_lips and 5 other fieldsHigh correlation
rusty_sputum is highly correlated with fast_heart_rate and 3 other fieldsHigh correlation
yellowing_of_eyes is highly correlated with abdominal_pain and 5 other fieldsHigh correlation
swelled_lymph_nodes is highly correlated with redness_of_eyes and 11 other fieldsHigh correlation
brittle_nails is highly correlated with abnormal_menstruation and 10 other fieldsHigh correlation
bloody_stool is highly correlated with constipation and 5 other fieldsHigh correlation
excessive_hunger is highly correlated with fluid_overload and 4 other fieldsHigh correlation
fluid_overload is highly correlated with constipation and 131 other fieldsHigh correlation
inflammatory_nails is highly correlated with skin_peeling and 4 other fieldsHigh correlation
pain_in_anal_region is highly correlated with constipation and 5 other fieldsHigh correlation
breathlessness is highly correlated with sweating and 5 other fieldsHigh correlation
bladder_discomfort is highly correlated with continuous_feel_of_urine and 4 other fieldsHigh correlation
pain_behind_the_eyes is highly correlated with back_pain and 3 other fieldsHigh correlation
dehydration is highly correlated with sunken_eyes and 2 other fieldsHigh correlation
unsteadiness is highly correlated with spinning_movements and 3 other fieldsHigh correlation
muscle_wasting is highly correlated with fluid_overload and 3 other fieldsHigh correlation
fluid_overload.1 is highly correlated with fluid_overload and 4 other fieldsHigh correlation
weight_gain is highly correlated with abnormal_menstruation and 10 other fieldsHigh correlation
puffy_face_and_eyes is highly correlated with abnormal_menstruation and 10 other fieldsHigh correlation
lethargy is highly correlated with fluid_overload and 1 other fieldsHigh correlation
yellowish_skin is highly correlated with abdominal_pain and 5 other fieldsHigh correlation
swelling_of_stomach is highly correlated with fluid_overload and 4 other fieldsHigh correlation
cough is highly correlated with phlegm and 4 other fieldsHigh correlation
acidity is highly correlated with fluid_overload and 3 other fieldsHigh correlation
ulcers_on_tongue is highly correlated with fluid_overload and 3 other fieldsHigh correlation
small_dents_in_nails is highly correlated with skin_peeling and 4 other fieldsHigh correlation
toxic_look_(typhos) is highly correlated with constipation and 3 other fieldsHigh correlation
coma is highly correlated with acute_liver_failure and 3 other fieldsHigh correlation
altered_sensorium is highly correlated with fluid_overload and 2 other fieldsHigh correlation
history_of_alcohol_consumption is highly correlated with fluid_overload and 4 other fieldsHigh correlation
swollen_extremeties is highly correlated with abnormal_menstruation and 10 other fieldsHigh correlation
blurred_and_distorted_vision is highly correlated with increased_appetite and 11 other fieldsHigh correlation
loss_of_smell is highly correlated with redness_of_eyes and 9 other fieldsHigh correlation
cramps is highly correlated with bruising and 6 other fieldsHigh correlation
stomach_bleeding is highly correlated with acute_liver_failure and 3 other fieldsHigh correlation
extra_marital_contacts is highly correlated with fluid_overload and 3 other fieldsHigh correlation
nodal_skin_eruptions is highly correlated with dischromic _patches and 2 other fieldsHigh correlation
red_sore_around_nose is highly correlated with yellow_crust_ooze and 3 other fieldsHigh correlation
knee_pain is highly correlated with swelling_joints and 5 other fieldsHigh correlation
sinus_pressure is highly correlated with redness_of_eyes and 9 other fieldsHigh correlation
visual_disturbances is highly correlated with indigestion and 6 other fieldsHigh correlation
skin_rash is highly correlated with fluid_overload and 1 other fieldsHigh correlation
swollen_blood_vessels is highly correlated with bruising and 6 other fieldsHigh correlation
swollen_legs is highly correlated with bruising and 6 other fieldsHigh correlation
obesity is highly correlated with bruising and 9 other fieldsHigh correlation
stiff_neck is highly correlated with fluid_overload and 3 other fieldsHigh correlation
mucoid_sputum is highly correlated with family_history and 2 other fieldsHigh correlation
restlessness is highly correlated with increased_appetite and 6 other fieldsHigh correlation
cold_hands_and_feets is highly correlated with abnormal_menstruation and 10 other fieldsHigh correlation
pain_during_bowel_movements is highly correlated with constipation and 5 other fieldsHigh correlation
chest_pain is highly correlated with phlegm and 4 other fieldsHigh correlation
distention_of_abdomen is highly correlated with fluid_overload and 4 other fieldsHigh correlation
internal_itching is highly correlated with indigestion and 3 other fieldsHigh correlation
movement_stiffness is highly correlated with muscle_weakness and 5 other fieldsHigh correlation
blister is highly correlated with yellow_crust_ooze and 3 other fieldsHigh correlation
lack_of_concentration is highly correlated with dizziness and 3 other fieldsHigh correlation
neck_pain is highly correlated with weakness_in_limbs and 4 other fieldsHigh correlation
mood_swings is highly correlated with abnormal_menstruation and 9 other fieldsHigh correlation
mild_fever is highly correlated with blood_in_sputum and 3 other fieldsHigh correlation
malaise is highly correlated with chills and 5 other fieldsHigh correlation
prominent_veins_on_calf is highly correlated with bruising and 6 other fieldsHigh correlation
headache is highly correlated with fluid_overload and 1 other fieldsHigh correlation
runny_nose is highly correlated with redness_of_eyes and 9 other fieldsHigh correlation
scurring is highly correlated with pus_filled_pimples and 3 other fieldsHigh correlation
burning_micturition is highly correlated with continuous_feel_of_urine and 5 other fieldsHigh correlation
patches_in_throat is highly correlated with fluid_overload and 3 other fieldsHigh correlation
irritability is highly correlated with abnormal_menstruation and 6 other fieldsHigh correlation
congestion is highly correlated with redness_of_eyes and 9 other fieldsHigh correlation
enlarged_thyroid is highly correlated with abnormal_menstruation and 10 other fieldsHigh correlation
stomach_pain is highly correlated with spotting_ urination and 3 other fieldsHigh correlation
hip_joint_pain is highly correlated with swelling_joints and 5 other fieldsHigh correlation
anxiety is highly correlated with drying_and_tingling_lips and 5 other fieldsHigh correlation
prognosis is highly correlated with constipation and 131 other fieldsHigh correlation
shivering is highly correlated with watering_from_eyes and 3 other fieldsHigh correlation
fatigue is highly correlated with fluid_overload and 1 other fieldsHigh correlation
irritation_in_anus is highly correlated with constipation and 5 other fieldsHigh correlation
weakness_of_one_body_side is highly correlated with fluid_overload and 2 other fieldsHigh correlation
itching is highly correlated with spotting_ urination and 4 other fieldsHigh correlation
skin_rash is highly correlated with pain_behind_the_eyes and 2 other fieldsHigh correlation
nodal_skin_eruptions is highly correlated with dischromic _patches and 1 other fieldsHigh correlation
continuous_sneezing is highly correlated with shivering and 11 other fieldsHigh correlation
shivering is highly correlated with continuous_sneezing and 2 other fieldsHigh correlation
chills is highly correlated with continuous_sneezing and 21 other fieldsHigh correlation
joint_pain is highly correlated with dark_urine and 14 other fieldsHigh correlation
stomach_pain is highly correlated with acidity and 4 other fieldsHigh correlation
acidity is highly correlated with stomach_pain and 7 other fieldsHigh correlation
ulcers_on_tongue is highly correlated with stomach_pain and 4 other fieldsHigh correlation
muscle_wasting is highly correlated with patches_in_throat and 2 other fieldsHigh correlation
vomiting is highly correlated with nausea and 2 other fieldsHigh correlation
burning_micturition is highly correlated with stomach_pain and 5 other fieldsHigh correlation
spotting_ urination is highly correlated with itching and 3 other fieldsHigh correlation
fatigue is highly correlated with weight_loss and 4 other fieldsHigh correlation
weight_gain is highly correlated with cold_hands_and_feets and 11 other fieldsHigh correlation
anxiety is highly correlated with sweating and 7 other fieldsHigh correlation
cold_hands_and_feets is highly correlated with weight_gain and 11 other fieldsHigh correlation
mood_swings is highly correlated with weight_gain and 13 other fieldsHigh correlation
weight_loss is highly correlated with fatigue and 7 other fieldsHigh correlation
restlessness is highly correlated with mood_swings and 11 other fieldsHigh correlation
lethargy is highly correlated with fatigue and 13 other fieldsHigh correlation
patches_in_throat is highly correlated with muscle_wasting and 2 other fieldsHigh correlation
irregular_sugar_level is highly correlated with weight_loss and 8 other fieldsHigh correlation
cough is highly correlated with chills and 17 other fieldsHigh correlation
high_fever is highly correlated with chills and 7 other fieldsHigh correlation
sunken_eyes is highly correlated with dehydration and 2 other fieldsHigh correlation
breathlessness is highly correlated with cough and 7 other fieldsHigh correlation
sweating is highly correlated with chills and 11 other fieldsHigh correlation
dehydration is highly correlated with sunken_eyes and 2 other fieldsHigh correlation
indigestion is highly correlated with acidity and 7 other fieldsHigh correlation
headache is highly correlated with chills and 3 other fieldsHigh correlation
yellowish_skin is highly correlated with dark_urine and 5 other fieldsHigh correlation
dark_urine is highly correlated with joint_pain and 11 other fieldsHigh correlation
nausea is highly correlated with joint_pain and 7 other fieldsHigh correlation
loss_of_appetite is highly correlated with joint_pain and 9 other fieldsHigh correlation
pain_behind_the_eyes is highly correlated with skin_rash and 7 other fieldsHigh correlation
back_pain is highly correlated with pain_behind_the_eyes and 4 other fieldsHigh correlation
constipation is highly correlated with pain_during_bowel_movements and 6 other fieldsHigh correlation
abdominal_pain is highly correlated with vomiting and 6 other fieldsHigh correlation
diarrhoea is highly correlated with sunken_eyes and 5 other fieldsHigh correlation
mild_fever is highly correlated with loss_of_appetite and 6 other fieldsHigh correlation
yellow_urine is highly correlated with itching and 7 other fieldsHigh correlation
yellowing_of_eyes is highly correlated with joint_pain and 14 other fieldsHigh correlation
acute_liver_failure is highly correlated with joint_pain and 5 other fieldsHigh correlation
swelling_of_stomach is highly correlated with distention_of_abdomen and 3 other fieldsHigh correlation
swelled_lymph_nodes is highly correlated with continuous_sneezing and 16 other fieldsHigh correlation
malaise is highly correlated with chills and 22 other fieldsHigh correlation
blurred_and_distorted_vision is highly correlated with acidity and 16 other fieldsHigh correlation
phlegm is highly correlated with continuous_sneezing and 18 other fieldsHigh correlation
throat_irritation is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
redness_of_eyes is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
sinus_pressure is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
runny_nose is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
congestion is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
chest_pain is highly correlated with chills and 16 other fieldsHigh correlation
weakness_in_limbs is highly correlated with back_pain and 4 other fieldsHigh correlation
fast_heart_rate is highly correlated with mood_swings and 7 other fieldsHigh correlation
pain_during_bowel_movements is highly correlated with constipation and 4 other fieldsHigh correlation
pain_in_anal_region is highly correlated with constipation and 4 other fieldsHigh correlation
bloody_stool is highly correlated with constipation and 4 other fieldsHigh correlation
irritation_in_anus is highly correlated with constipation and 4 other fieldsHigh correlation
neck_pain is highly correlated with back_pain and 8 other fieldsHigh correlation
dizziness is highly correlated with weight_gain and 13 other fieldsHigh correlation
cramps is highly correlated with bruising and 5 other fieldsHigh correlation
bruising is highly correlated with cramps and 5 other fieldsHigh correlation
obesity is highly correlated with restlessness and 10 other fieldsHigh correlation
swollen_legs is highly correlated with cramps and 5 other fieldsHigh correlation
swollen_blood_vessels is highly correlated with cramps and 5 other fieldsHigh correlation
puffy_face_and_eyes is highly correlated with weight_gain and 11 other fieldsHigh correlation
enlarged_thyroid is highly correlated with weight_gain and 11 other fieldsHigh correlation
brittle_nails is highly correlated with weight_gain and 11 other fieldsHigh correlation
swollen_extremeties is highly correlated with weight_gain and 11 other fieldsHigh correlation
excessive_hunger is highly correlated with anxiety and 12 other fieldsHigh correlation
extra_marital_contacts is highly correlated with muscle_wasting and 2 other fieldsHigh correlation
drying_and_tingling_lips is highly correlated with anxiety and 7 other fieldsHigh correlation
slurred_speech is highly correlated with anxiety and 7 other fieldsHigh correlation
knee_pain is highly correlated with joint_pain and 5 other fieldsHigh correlation
hip_joint_pain is highly correlated with joint_pain and 5 other fieldsHigh correlation
muscle_weakness is highly correlated with mood_swings and 8 other fieldsHigh correlation
stiff_neck is highly correlated with acidity and 9 other fieldsHigh correlation
swelling_joints is highly correlated with neck_pain and 7 other fieldsHigh correlation
movement_stiffness is highly correlated with muscle_weakness and 4 other fieldsHigh correlation
spinning_movements is highly correlated with loss_of_balance and 2 other fieldsHigh correlation
loss_of_balance is highly correlated with weakness_in_limbs and 6 other fieldsHigh correlation
unsteadiness is highly correlated with spinning_movements and 2 other fieldsHigh correlation
weakness_of_one_body_side is highly correlated with altered_sensorium and 1 other fieldsHigh correlation
loss_of_smell is highly correlated with continuous_sneezing and 13 other fieldsHigh correlation
bladder_discomfort is highly correlated with burning_micturition and 3 other fieldsHigh correlation
foul_smell_of urine is highly correlated with burning_micturition and 3 other fieldsHigh correlation
continuous_feel_of_urine is highly correlated with burning_micturition and 3 other fieldsHigh correlation
passage_of_gases is highly correlated with indigestion and 2 other fieldsHigh correlation
internal_itching is highly correlated with indigestion and 2 other fieldsHigh correlation
toxic_look_(typhos) is highly correlated with chills and 4 other fieldsHigh correlation
depression is highly correlated with acidity and 15 other fieldsHigh correlation
irritability is highly correlated with weight_gain and 16 other fieldsHigh correlation
muscle_pain is highly correlated with chills and 11 other fieldsHigh correlation
altered_sensorium is highly correlated with weakness_of_one_body_side and 1 other fieldsHigh correlation
red_spots_over_body is highly correlated with skin_rash and 9 other fieldsHigh correlation
belly_pain is highly correlated with chills and 4 other fieldsHigh correlation
abnormal_menstruation is highly correlated with weight_gain and 13 other fieldsHigh correlation
dischromic _patches is highly correlated with nodal_skin_eruptions and 1 other fieldsHigh correlation
watering_from_eyes is highly correlated with continuous_sneezing and 2 other fieldsHigh correlation
increased_appetite is highly correlated with weight_loss and 8 other fieldsHigh correlation
polyuria is highly correlated with weight_loss and 8 other fieldsHigh correlation
family_history is highly correlated with mucoid_sputum and 1 other fieldsHigh correlation
mucoid_sputum is highly correlated with cough and 3 other fieldsHigh correlation
rusty_sputum is highly correlated with chills and 8 other fieldsHigh correlation
lack_of_concentration is highly correlated with dizziness and 2 other fieldsHigh correlation
visual_disturbances is highly correlated with acidity and 7 other fieldsHigh correlation
receiving_blood_transfusion is highly correlated with itching and 7 other fieldsHigh correlation
receiving_unsterile_injections is highly correlated with itching and 7 other fieldsHigh correlation
coma is highly correlated with joint_pain and 5 other fieldsHigh correlation
stomach_bleeding is highly correlated with joint_pain and 5 other fieldsHigh correlation
distention_of_abdomen is highly correlated with swelling_of_stomach and 3 other fieldsHigh correlation
history_of_alcohol_consumption is highly correlated with swelling_of_stomach and 3 other fieldsHigh correlation
fluid_overload.1 is highly correlated with swelling_of_stomach and 3 other fieldsHigh correlation
blood_in_sputum is highly correlated with chills and 11 other fieldsHigh correlation
prominent_veins_on_calf is highly correlated with cramps and 5 other fieldsHigh correlation
palpitations is highly correlated with anxiety and 7 other fieldsHigh correlation
painful_walking is highly correlated with neck_pain and 7 other fieldsHigh correlation
pus_filled_pimples is highly correlated with blackheads and 2 other fieldsHigh correlation
blackheads is highly correlated with pus_filled_pimples and 2 other fieldsHigh correlation
scurring is highly correlated with pus_filled_pimples and 2 other fieldsHigh correlation
skin_peeling is highly correlated with joint_pain and 4 other fieldsHigh correlation
silver_like_dusting is highly correlated with joint_pain and 4 other fieldsHigh correlation
small_dents_in_nails is highly correlated with joint_pain and 4 other fieldsHigh correlation
inflammatory_nails is highly correlated with joint_pain and 4 other fieldsHigh correlation
blister is highly correlated with red_sore_around_nose and 2 other fieldsHigh correlation
red_sore_around_nose is highly correlated with blister and 2 other fieldsHigh correlation
yellow_crust_ooze is highly correlated with blister and 2 other fieldsHigh correlation
prognosis is highly correlated with itching and 130 other fieldsHigh correlation
Unnamed: 133 has 4920 (100.0%) missing values Missing
prognosis is uniformly distributed Uniform
Unnamed: 133 is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2022-11-21 19:31:39.195768
Analysis finished2022-11-21 19:34:10.064714
Duration2 minutes and 30.87 seconds
Software versionpandas-profiling v3.1.0
Download configurationconfig.json

Variables

itching
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4242 
1
678 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
04242
86.2%
1678
 
13.8%

Length

2022-11-22T01:04:10.260050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:10.415492image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04242
86.2%
1678
 
13.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

skin_rash
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4134 
1
786 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
04134
84.0%
1786
 
16.0%

Length

2022-11-22T01:04:12.897228image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:13.035424image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04134
84.0%
1786
 
16.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

nodal_skin_eruptions
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row0
5th row1

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:13.173453image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:13.292110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

continuous_sneezing
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Length

2022-11-22T01:04:13.450050image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:13.565037image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

shivering
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:13.699157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:13.801654image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

chills
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4122 
1
798 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04122
83.8%
1798
 
16.2%

Length

2022-11-22T01:04:13.947849image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:14.070033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04122
83.8%
1798
 
16.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

joint_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4236 
1
684 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04236
86.1%
1684
 
13.9%

Length

2022-11-22T01:04:14.195250image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:14.307877image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04236
86.1%
1684
 
13.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

stomach_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Length

2022-11-22T01:04:14.456463image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:14.569995image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

acidity
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Length

2022-11-22T01:04:14.708058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:14.818703image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

ulcers_on_tongue
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:15.011695image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:15.153721image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

muscle_wasting
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:15.315458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:15.473869image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

vomiting
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3006 
1
1914 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03006
61.1%
11914
38.9%

Length

2022-11-22T01:04:15.655779image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:15.804287image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
03006
61.1%
11914
38.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

burning_micturition
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4704 
1
 
216

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04704
95.6%
1216
 
4.4%

Length

2022-11-22T01:04:15.954689image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:16.184016image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04704
95.6%
1216
 
4.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

spotting_ urination
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:16.310653image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:16.426923image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

fatigue
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
2988 
1
1932 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
02988
60.7%
11932
39.3%

Length

2022-11-22T01:04:16.574996image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:16.686835image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
02988
60.7%
11932
39.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

weight_gain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:16.827078image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:16.946897image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

anxiety
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:17.384212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:17.496954image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

cold_hands_and_feets
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:17.626422image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:17.748277image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

mood_swings
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-11-22T01:04:17.879839image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:18.015797image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

weight_loss
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4464 
1
456 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04464
90.7%
1456
 
9.3%

Length

2022-11-22T01:04:18.160832image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:18.286446image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04464
90.7%
1456
 
9.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

restlessness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-11-22T01:04:18.414753image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:18.534852image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

lethargy
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4464 
1
456 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04464
90.7%
1456
 
9.3%

Length

2022-11-22T01:04:18.662742image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:18.797120image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04464
90.7%
1456
 
9.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

patches_in_throat
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:18.978078image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:19.132726image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

irregular_sugar_level
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:19.318153image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:19.505211image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

cough
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4356 
1
564 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04356
88.5%
1564
 
11.5%

Length

2022-11-22T01:04:19.690615image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:19.850845image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04356
88.5%
1564
 
11.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

high_fever
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3558 
1
1362 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03558
72.3%
11362
 
27.7%

Length

2022-11-22T01:04:20.047879image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:20.221095image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
03558
72.3%
11362
 
27.7%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

sunken_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:20.397724image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:20.530820image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

breathlessness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4470 
1
450 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04470
90.9%
1450
 
9.1%

Length

2022-11-22T01:04:20.709750image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:20.857965image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04470
90.9%
1450
 
9.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

sweating
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4242 
1
678 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04242
86.2%
1678
 
13.8%

Length

2022-11-22T01:04:21.027210image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:21.196892image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04242
86.2%
1678
 
13.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

dehydration
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:21.363380image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:21.492058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

indigestion
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4698 
1
 
222

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Length

2022-11-22T01:04:21.673255image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:21.841370image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04698
95.5%
1222
 
4.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

headache
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3786 
1
1134 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03786
77.0%
11134
 
23.0%

Length

2022-11-22T01:04:22.035883image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:22.203542image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
03786
77.0%
11134
 
23.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

yellowish_skin
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4008 
1
912 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04008
81.5%
1912
 
18.5%

Length

2022-11-22T01:04:22.387908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:22.519191image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04008
81.5%
1912
 
18.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

dark_urine
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4350 
1
570 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04350
88.4%
1570
 
11.6%

Length

2022-11-22T01:04:22.692605image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:22.831957image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04350
88.4%
1570
 
11.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

nausea
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3774 
1
1146 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03774
76.7%
11146
 
23.3%

Length

2022-11-22T01:04:23.016099image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:23.198212image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
03774
76.7%
11146
 
23.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

loss_of_appetite
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3768 
1
1152 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03768
76.6%
11152
 
23.4%

Length

2022-11-22T01:04:23.403843image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:23.555982image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
03768
76.6%
11152
 
23.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pain_behind_the_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:23.723831image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:23.866406image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

back_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-11-22T01:04:24.056643image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:24.239043image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

constipation
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-11-22T01:04:24.448555image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:24.582328image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

abdominal_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
3888 
1
1032 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
03888
79.0%
11032
 
21.0%

Length

2022-11-22T01:04:24.736689image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:24.875767image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
03888
79.0%
11032
 
21.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

diarrhoea
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4356 
1
564 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04356
88.5%
1564
 
11.5%

Length

2022-11-22T01:04:25.308292image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:25.448025image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04356
88.5%
1564
 
11.5%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

mild_fever
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4566 
1
 
354

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04566
92.8%
1354
 
7.2%

Length

2022-11-22T01:04:25.583826image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:25.703606image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04566
92.8%
1354
 
7.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

yellow_urine
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:25.843666image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:25.953310image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

yellowing_of_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4104 
1
816 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04104
83.4%
1816
 
16.6%

Length

2022-11-22T01:04:26.088893image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:26.213670image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04104
83.4%
1816
 
16.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

acute_liver_failure
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:26.360862image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:26.472917image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

fluid_overload
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4920 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04920
100.0%

Length

2022-11-22T01:04:26.598808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:26.720911image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04920
100.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swelling_of_stomach
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:26.839144image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:26.941349image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swelled_lymph_nodes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4572 
1
 
348

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04572
92.9%
1348
 
7.1%

Length

2022-11-22T01:04:27.080867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:27.209810image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04572
92.9%
1348
 
7.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

malaise
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4218 
1
702 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04218
85.7%
1702
 
14.3%

Length

2022-11-22T01:04:27.358176image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:27.489215image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04218
85.7%
1702
 
14.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

blurred_and_distorted_vision
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4578 
1
 
342

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04578
93.0%
1342
 
7.0%

Length

2022-11-22T01:04:27.609697image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:27.747821image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04578
93.0%
1342
 
7.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

phlegm
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4566 
1
 
354

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04566
92.8%
1354
 
7.2%

Length

2022-11-22T01:04:27.891002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:28.028846image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04566
92.8%
1354
 
7.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

throat_irritation
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:28.168666image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:28.305228image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

redness_of_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:28.430521image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:28.590425image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

sinus_pressure
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:28.752058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:28.885981image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

runny_nose
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:29.055077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:29.207108image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

congestion
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:29.363488image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:29.494185image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

chest_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4224 
1
696 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04224
85.9%
1696
 
14.1%

Length

2022-11-22T01:04:29.661005image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:29.813100image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04224
85.9%
1696
 
14.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

weakness_in_limbs
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:29.958264image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:30.094548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

fast_heart_rate
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Length

2022-11-22T01:04:30.226664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:30.358899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pain_during_bowel_movements
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:30.488628image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:30.616916image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pain_in_anal_region
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:30.750643image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:30.871103image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

bloody_stool
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:31.025575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:31.133231image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

irritation_in_anus
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:31.292128image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:31.436908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

neck_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-11-22T01:04:31.583410image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:31.734848image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

dizziness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4584 
1
 
336

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04584
93.2%
1336
 
6.8%

Length

2022-11-22T01:04:32.166677image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:32.298312image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04584
93.2%
1336
 
6.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

cramps
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:32.438995image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:32.559111image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

bruising
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:32.675508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:32.792797image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

obesity
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-11-22T01:04:32.942157image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:33.056302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swollen_legs
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:33.189186image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:33.314929image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swollen_blood_vessels
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:33.455486image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:33.580110image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

puffy_face_and_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:33.695470image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:33.827323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

enlarged_thyroid
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:33.954199image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:34.068072image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

brittle_nails
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:34.197257image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:34.318462image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swollen_extremeties
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:34.469884image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:34.601840image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

excessive_hunger
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4458 
1
462 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04458
90.6%
1462
 
9.4%

Length

2022-11-22T01:04:34.750758image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:34.849896image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04458
90.6%
1462
 
9.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

extra_marital_contacts
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:34.982740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:35.098894image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

drying_and_tingling_lips
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:35.232121image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:35.354371image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

slurred_speech
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:35.496890image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:35.616536image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

knee_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:35.765192image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:35.884438image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

hip_joint_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:35.999034image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:36.102676image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

muscle_weakness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Length

2022-11-22T01:04:36.226608image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:36.358904image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

stiff_neck
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-11-22T01:04:36.513391image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:36.658939image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

swelling_joints
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-11-22T01:04:36.794946image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:36.896480image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

movement_stiffness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:37.030855image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:37.139072image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

spinning_movements
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:37.252405image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:37.370647image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

loss_of_balance
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4578 
1
 
342

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04578
93.0%
1342
 
7.0%

Length

2022-11-22T01:04:37.515117image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:37.646779image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04578
93.0%
1342
 
7.0%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

unsteadiness
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:37.787920image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:37.908242image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

weakness_of_one_body_side
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:38.046809image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:38.179076image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

loss_of_smell
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:38.626736image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:38.746180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

bladder_discomfort
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:38.896120image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:39.020185image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

foul_smell_of urine
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4818 
1
 
102

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04818
97.9%
1102
 
2.1%

Length

2022-11-22T01:04:39.163365image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:39.269548image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04818
97.9%
1102
 
2.1%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

continuous_feel_of_urine
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:39.391713image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:39.508008image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

passage_of_gases
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:39.614974image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:39.721903image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

internal_itching
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:39.851997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:39.979061image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

toxic_look_(typhos)
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:40.120382image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:40.258708image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

depression
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Length

2022-11-22T01:04:40.410508image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:40.519772image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

irritability
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4446 
1
474 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04446
90.4%
1474
 
9.6%

Length

2022-11-22T01:04:40.648878image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:40.781008image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04446
90.4%
1474
 
9.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

muscle_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4446 
1
474 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04446
90.4%
1474
 
9.6%

Length

2022-11-22T01:04:40.934875image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:41.060815image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04446
90.4%
1474
 
9.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

altered_sensorium
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:41.205475image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:41.341060image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

red_spots_over_body
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4686 
1
 
234

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Length

2022-11-22T01:04:41.479494image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:41.600363image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04686
95.2%
1234
 
4.8%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

belly_pain
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:41.746715image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:41.880080image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

abnormal_menstruation
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4680 
1
 
240

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04680
95.1%
1240
 
4.9%

Length

2022-11-22T01:04:42.035153image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:42.160511image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04680
95.1%
1240
 
4.9%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

dischromic _patches
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:42.293339image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:42.400053image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

watering_from_eyes
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:42.524101image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:42.653373image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

increased_appetite
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:42.766608image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:42.889781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

polyuria
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:43.010033image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:43.140684image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

family_history
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-11-22T01:04:43.289603image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:43.408997image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

mucoid_sputum
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:43.549172image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:43.670220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

rusty_sputum
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:43.813699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:43.956836image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

lack_of_concentration
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:44.100062image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:44.216684image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

visual_disturbances
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:44.350383image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:44.479012image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

receiving_blood_transfusion
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:44.651200image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:44.800848image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

receiving_unsterile_injections
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:45.249948image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:45.373616image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

coma
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:45.524824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:45.655177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

stomach_bleeding
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:45.785824image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:45.893152image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

distention_of_abdomen
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:46.025783image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:46.149600image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

history_of_alcohol_consumption
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:46.299700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:46.413214image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

fluid_overload.1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:46.571664image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:46.727822image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

blood_in_sputum
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:46.864389image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:47.004603image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

prominent_veins_on_calf
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:47.119728image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:47.236809image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

palpitations
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4800 
1
 
120

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Length

2022-11-22T01:04:47.383153image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:47.489776image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04800
97.6%
1120
 
2.4%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

painful_walking
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4692 
1
 
228

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Length

2022-11-22T01:04:47.628686image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:47.768588image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04692
95.4%
1228
 
4.6%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

pus_filled_pimples
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:47.903814image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:48.010781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

blackheads
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:48.145107image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:48.265477image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

scurring
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4812 
1
 
108

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Length

2022-11-22T01:04:48.418876image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:48.549099image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04812
97.8%
1108
 
2.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

skin_peeling
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:48.700965image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:48.814546image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

silver_like_dusting
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:48.958000image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:49.111111image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

small_dents_in_nails
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:49.270782image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:49.555251image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

inflammatory_nails
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:49.731807image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:49.881871image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

blister
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:50.026334image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:50.130027image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

red_sore_around_nose
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:50.264344image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:50.379052image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

yellow_crust_ooze
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
0
4806 
1
 
114

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Length

2022-11-22T01:04:50.488198image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2022-11-22T01:04:50.667054image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
ValueCountFrequency (%)
04806
97.7%
1114
 
2.3%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

prognosis
Categorical

HIGH CORRELATION
HIGH CORRELATION
UNIFORM

Distinct41
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size38.6 KiB
Hepatitis B
 
120
Allergy
 
120
Impetigo
 
120
Urinary tract infection
 
120
Hypothyroidism
 
120
Other values (36)
4320 

Length

Max length39
Median length11
Mean length13.12195122
Min length4

Characters and Unicode

Total characters0
Distinct characters0
Distinct categories0 ?
Distinct scripts0 ?
Distinct blocks0 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFungal infection
2nd rowFungal infection
3rd rowFungal infection
4th rowFungal infection
5th rowFungal infection

Common Values

ValueCountFrequency (%)
Hepatitis B120
 
2.4%
Allergy120
 
2.4%
Impetigo120
 
2.4%
Urinary tract infection120
 
2.4%
Hypothyroidism120
 
2.4%
Pneumonia120
 
2.4%
Hepatitis D120
 
2.4%
Chicken pox120
 
2.4%
Acne120
 
2.4%
Dengue120
 
2.4%
Other values (31)3720
75.6%

Length

2022-11-22T01:04:50.839566image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
hepatitis720
 
9.1%
infection240
 
3.0%
vertigo240
 
3.0%
psoriasis120
 
1.5%
reaction120
 
1.5%
drug120
 
1.5%
cholestasis120
 
1.5%
chronic120
 
1.5%
spondylosis120
 
1.5%
cervical120
 
1.5%
Other values (49)5880
74.2%

Most occurring characters

ValueCountFrequency (%)
No values found.

Most occurring categories

ValueCountFrequency (%)
No values found.

Most frequent character per category

Most occurring scripts

ValueCountFrequency (%)
No values found.

Most frequent character per script

Most occurring blocks

ValueCountFrequency (%)
No values found.

Most frequent character per block

Unnamed: 133
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing4920
Missing (%)100.0%
Memory size38.6 KiB

Correlations

2022-11-22T01:04:51.885057image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-11-22T01:05:08.973820image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-11-22T01:05:26.281868image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-11-22T01:05:43.233769image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.
2022-11-22T01:06:01.269867image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-11-22T01:04:01.426641image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2022-11-22T01:04:07.322106image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

itchingskin_rashnodal_skin_eruptionscontinuous_sneezingshiveringchillsjoint_painstomach_painacidityulcers_on_tonguemuscle_wastingvomitingburning_micturitionspotting_ urinationfatigueweight_gainanxietycold_hands_and_feetsmood_swingsweight_lossrestlessnesslethargypatches_in_throatirregular_sugar_levelcoughhigh_feversunken_eyesbreathlessnesssweatingdehydrationindigestionheadacheyellowish_skindark_urinenausealoss_of_appetitepain_behind_the_eyesback_painconstipationabdominal_paindiarrhoeamild_feveryellow_urineyellowing_of_eyesacute_liver_failurefluid_overloadswelling_of_stomachswelled_lymph_nodesmalaiseblurred_and_distorted_visionphlegmthroat_irritationredness_of_eyessinus_pressurerunny_nosecongestionchest_painweakness_in_limbsfast_heart_ratepain_during_bowel_movementspain_in_anal_regionbloody_stoolirritation_in_anusneck_paindizzinesscrampsbruisingobesityswollen_legsswollen_blood_vesselspuffy_face_and_eyesenlarged_thyroidbrittle_nailsswollen_extremetiesexcessive_hungerextra_marital_contactsdrying_and_tingling_lipsslurred_speechknee_painhip_joint_painmuscle_weaknessstiff_neckswelling_jointsmovement_stiffnessspinning_movementsloss_of_balanceunsteadinessweakness_of_one_body_sideloss_of_smellbladder_discomfortfoul_smell_of urinecontinuous_feel_of_urinepassage_of_gasesinternal_itchingtoxic_look_(typhos)depressionirritabilitymuscle_painaltered_sensoriumred_spots_over_bodybelly_painabnormal_menstruationdischromic _patcheswatering_from_eyesincreased_appetitepolyuriafamily_historymucoid_sputumrusty_sputumlack_of_concentrationvisual_disturbancesreceiving_blood_transfusionreceiving_unsterile_injectionscomastomach_bleedingdistention_of_abdomenhistory_of_alcohol_consumptionfluid_overload.1blood_in_sputumprominent_veins_on_calfpalpitationspainful_walkingpus_filled_pimplesblackheadsscurringskin_peelingsilver_like_dustingsmall_dents_in_nailsinflammatory_nailsblisterred_sore_around_noseyellow_crust_oozeprognosisUnnamed: 133
0111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
1011000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
2101000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
3110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
4111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000Fungal infectionNaN
5011000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
6101000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
7110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN
8111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000Fungal infectionNaN
9111000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000100000000000000000000000000000Fungal infectionNaN

Last rows

itchingskin_rashnodal_skin_eruptionscontinuous_sneezingshiveringchillsjoint_painstomach_painacidityulcers_on_tonguemuscle_wastingvomitingburning_micturitionspotting_ urinationfatigueweight_gainanxietycold_hands_and_feetsmood_swingsweight_lossrestlessnesslethargypatches_in_throatirregular_sugar_levelcoughhigh_feversunken_eyesbreathlessnesssweatingdehydrationindigestionheadacheyellowish_skindark_urinenausealoss_of_appetitepain_behind_the_eyesback_painconstipationabdominal_paindiarrhoeamild_feveryellow_urineyellowing_of_eyesacute_liver_failurefluid_overloadswelling_of_stomachswelled_lymph_nodesmalaiseblurred_and_distorted_visionphlegmthroat_irritationredness_of_eyessinus_pressurerunny_nosecongestionchest_painweakness_in_limbsfast_heart_ratepain_during_bowel_movementspain_in_anal_regionbloody_stoolirritation_in_anusneck_paindizzinesscrampsbruisingobesityswollen_legsswollen_blood_vesselspuffy_face_and_eyesenlarged_thyroidbrittle_nailsswollen_extremetiesexcessive_hungerextra_marital_contactsdrying_and_tingling_lipsslurred_speechknee_painhip_joint_painmuscle_weaknessstiff_neckswelling_jointsmovement_stiffnessspinning_movementsloss_of_balanceunsteadinessweakness_of_one_body_sideloss_of_smellbladder_discomfortfoul_smell_of urinecontinuous_feel_of_urinepassage_of_gasesinternal_itchingtoxic_look_(typhos)depressionirritabilitymuscle_painaltered_sensoriumred_spots_over_bodybelly_painabnormal_menstruationdischromic _patcheswatering_from_eyesincreased_appetitepolyuriafamily_historymucoid_sputumrusty_sputumlack_of_concentrationvisual_disturbancesreceiving_blood_transfusionreceiving_unsterile_injectionscomastomach_bleedingdistention_of_abdomenhistory_of_alcohol_consumptionfluid_overload.1blood_in_sputumprominent_veins_on_calfpalpitationspainful_walkingpus_filled_pimplesblackheadsscurringskin_peelingsilver_like_dustingsmall_dents_in_nailsinflammatory_nailsblisterred_sore_around_noseyellow_crust_oozeprognosisUnnamed: 133
4910000000000000001101100100000000000000000000000000000000000000000010000011110000000000000000000001100001000000000000000000000000000000HypothyroidismNaN
4911000000000000001000111000000010000000000010000000000000000010000000000000001000001000000000000000100001000000000000000000000000000000HyperthyroidismNaN
4912000000000001001010000000000010010010000000000000010000000000000000000000001011000000000000000000100000000000000000000000100000000000HypoglycemiaNaN
4913000000100000000000000000000000000000000000000000000000000000000100000000000000110010000000000000000000000000000000000000010000000000OsteoarthristisNaN
4914000000000000000000000000000000000000000000000000000000000000000000000000000000001111000000000000000000000000000000000000010000000000ArthritisNaN
4915000000000001000000000000000000010010000000000000000000000000000000000000000000000000111000000000000000000000000000000000000000000000(vertigo) Paroymsal Positional VertigoNaN
4916010000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001110000000AcneNaN
4917000000000000100000000000000000000000000000000000000000000000000000000000000000000000000001110000000000000000000000000000000000000000Urinary tract infectionNaN
4918010000100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001111000PsoriasisNaN
4919010000000000000000000000010000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000111ImpetigoNaN

Duplicate rows

Most frequently occurring

itchingskin_rashnodal_skin_eruptionscontinuous_sneezingshiveringchillsjoint_painstomach_painacidityulcers_on_tonguemuscle_wastingvomitingburning_micturitionspotting_ urinationfatigueweight_gainanxietycold_hands_and_feetsmood_swingsweight_lossrestlessnesslethargypatches_in_throatirregular_sugar_levelcoughhigh_feversunken_eyesbreathlessnesssweatingdehydrationindigestionheadacheyellowish_skindark_urinenausealoss_of_appetitepain_behind_the_eyesback_painconstipationabdominal_paindiarrhoeamild_feveryellow_urineyellowing_of_eyesacute_liver_failurefluid_overloadswelling_of_stomachswelled_lymph_nodesmalaiseblurred_and_distorted_visionphlegmthroat_irritationredness_of_eyessinus_pressurerunny_nosecongestionchest_painweakness_in_limbsfast_heart_ratepain_during_bowel_movementspain_in_anal_regionbloody_stoolirritation_in_anusneck_paindizzinesscrampsbruisingobesityswollen_legsswollen_blood_vesselspuffy_face_and_eyesenlarged_thyroidbrittle_nailsswollen_extremetiesexcessive_hungerextra_marital_contactsdrying_and_tingling_lipsslurred_speechknee_painhip_joint_painmuscle_weaknessstiff_neckswelling_jointsmovement_stiffnessspinning_movementsloss_of_balanceunsteadinessweakness_of_one_body_sideloss_of_smellbladder_discomfortfoul_smell_of urinecontinuous_feel_of_urinepassage_of_gasesinternal_itchingtoxic_look_(typhos)depressionirritabilitymuscle_painaltered_sensoriumred_spots_over_bodybelly_painabnormal_menstruationdischromic _patcheswatering_from_eyesincreased_appetitepolyuriafamily_historymucoid_sputumrusty_sputumlack_of_concentrationvisual_disturbancesreceiving_blood_transfusionreceiving_unsterile_injectionscomastomach_bleedingdistention_of_abdomenhistory_of_alcohol_consumptionfluid_overload.1blood_in_sputumprominent_veins_on_calfpalpitationspainful_walkingpus_filled_pimplesblackheadsscurringskin_peelingsilver_like_dustingsmall_dents_in_nailsinflammatory_nailsblisterred_sore_around_noseyellow_crust_oozeprognosis# duplicates
7000000000000000000000000000000000000000000000000000000000000000000000000000000001111000000000000000000000000000000000000010000000000Arthritis90
17000000000000000000000000000000000000001000000000000000000001111000000000000000000000000000000000000000000000000000000000000000000000Dimorphic hemmorhoids(piles)90
163000000100000000000000000000000000000000000000000000000000000000100000000000000110010000000000000000000000000000000000000010000000000Osteoarthristis84
252010000100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001111000Psoriasis84
22000000000000000000000000000000000000010000000000000000000100000110000000000000000000010000000000000000000000000000000000000000000000Cervical spondylosis78
54000000000000001000000000000000001011000000010000000000000000000000000000000000000000000000000000000000000010000000000000000000000000Hepatitis C78
90000000000000100000000000000000000000000000000000000000000000000000000000000000000000000001110000000000000000000000000000000000000000Urinary tract infection78
100000000000001000000000000000000001000000100000010000000000000000000000000000000000000000000000000000000000000000000011100000000000000Alcoholic hepatitis78
105000000000001000000000000000000010000000000000000000000000000000000000000000000000000000100000000001000000000000000000000000000000000Paralysis (brain hemorrhage)78
110000000000001000000000000000000010010000000000000000000000000000000000000000000000000111000000000000000000000000000000000000000000000(vertigo) Paroymsal Positional Vertigo78